Schedules and Plans in the 4-Dimensional Map

Today when I use my GPS to plan a trip, I don’t tell anyone else about the details so they can include that in their planning. And that means I don’t have information about other people either, other than statistical predictions, or real-time traffic data.

So if I ask when is the best time to go to dinner so I don’t have to wait in line? Or when do I need to leave to get my preferred seat at the movie? Or how early do I have to leave to miss rush hour (and that’s a big deal when we are trying to get past New York City going to the Adirondacks J)? The GPS doesn’t help me.

In the 4-Dimensional Map I will enter my Planned Path, and my Personal Transport Vehicle will update it as we progress toward my destination. If enough people do this then I will have very good answers to all those questions. Actually the Autonomous Vehicles will enter the data for me, so we should have very good data.

A study 20 years ago showed that executive’s calendars were only correct about ½ the time in predicting where they would be. But as people become more dependent on smart-devices, our plans and schedules become more detailed and more accurate, even tracking changes.

As more systems join the 4-Dimensional Map we will get even better plans – more about this if future posts.

The 4-Dimensional Map can predict how early I need to leave to be sure I get to my 9 am meeting on time. 

Scheduling will evolve to include probabilistic estimates. For example, if I need to be in the O’Hare Hilton for a 9 am meeting on Tuesday with at least a 90% probability of getting there on time, I can take the 7 am shuttle from Newark Liberty airport. But if I want to be 95% sure I need to take the 6 am shuttle, and if I need to be 99% sure, I need to go out Monday night and stay overnight in the O’Hare Hilton – these calculations depend on all sorts of variables, including weather, on-time statistics for the flights, strikes against the airline, maintenance issues, how crowded the highways and airways will be, crowds at sports events in nearby arenas, shore traffic on summer weekends, etc.

The Autonomous Vehicle hierarchy means timing is important so that my Personal Mobility Vehicle doesn’t have to wait to join a Convoy, and that there is enough space on the Convoy Vehicles for me. Fortunately, this will be transparent to me because the Autonomous Vehicles automatically take this into account, as long as I tell my Personal Transport Vehicle where I want to go and when.

Planning and prediction become more important as we add the variety of Vehicles in the Autonomous Vehicle Hierarchy: Convoy Vehicles of different sizes and speeds, Personal Mobility Vehicles carrying people and other Autonomous Vehicles, and Mini-Mobility Vehicles carrying everything from fruit to medications.

For example, a Mini-Mobility Vehicle bringing my morning pills from the drug store may use several different Personal Mobility Vehicles and Convoy Vehicles on its rapid path to my breakfast table.

Nested Vehicles lead to nested Local Maps and nested Cloudlets. The Convoy Vehicles are communicating with each other so the Convoy functions properly. Within the Convoy, the Autonomous Vehicles being carried along are communicating with each other as a Cloudlet to maneuver within the Convoy Vehicles, and with the Convoy Vehicles to determine which Convoy Vehicle to be in to exit at the appropriate station, as part of En Route Sequencing. Nested Convoy Vehicles make this even more interesting.

In later Posts I will talk about optimizing paths through this complex rapidly moving web.

Next I want to talk about an application to help people who are wheelchair bound: an Autonomous Toileting System.

4-Dimensional Global Map

One of the challenges for successful Autonomous Vehicles is knowing where to go, following paths to get to there, and avoiding running into things along the way.

An article in the latest issue of Wired magazine on Mapping Mogadishu reminded me of ideas I had about 5 years ago on mapping. In Mogadishu the chaos has destroyed all the records of: people, property, taxes, businesses, everything. The hope is that by building a comprehensive map encompassing all these data, life will return to normal more quickly in Mogadishu.

My ideas were triggered by figuring out how a Personal Transport Vehicle would help my father get around in Charlestown. For example, getting to his table in the dining room required moving through a maze of people, tables, chairs, wheelchairs, and other Personal Transport Vehicles.

The advent of ubiquitous GPS and online maps has dramatically changed how we drive, but we still have to use a lot of concentration and knowledge to translate the line the GPS blithely draws on the screen into a continuous stream of steering, acceleration and braking controls to keep from joining the 40,000 annual dead or the 1,000,000 annual injured in car collisions.

Innovations like traffic prediction and alternate routing are still in their infancy. Recently, my GPS predicted a 12 minute delay on the highway I was just about to turn onto, so I accepted its recommendation to turn onto a side street instead: that took me down a 25 mph road, past 2 schools, which were just letting out; it took more than 12 minutes, and as I turned onto the highway, supposedly just at the end of the congestion, the highway was clear as far back as I could see.

But GPS and online maps aren’t any help at all for my father’s Personal Transport Vehicle getting to his table for dinner. The GPS doesn’t work very well indoors and its accuracy is at best a few feet, which isn’t very helpful when trying to get within 1 inch of the table. Further, the online maps don’t say anything about the layout of the hallways and doors inside Charlestown, much less the placement of tables and chairs, and even less where people are at any instant in time.

You may be thinking: that’s true, but the sensors on driverless cars will take care of that. Good thought, but it doesn’t work for several reasons: line-of-sight, accuracy, 3-dimensionality, and time or the 4^th-dimension.

Line-of-sight: when looking at a mass of people, you can’t see what is hidden behind other people or other obstacles. (Radar isn’t very good at localizing people, and I don’t think blasting everyone with continuous radar will be very popular anyway.) Thus the path you need to follow is probably not even visible from where you are standing, unless you are very tall and the crowd isn’t very big. J

Accuracy: you probably don’t want vehicles coming within about 6” of each other or of people, or even farther at more than walking speed. And my father wants to get within an inch of the table. That resolution requires good optics, with a steady mount and other technical characteristics, such as a long baseline for stereoscopic vision. Not impossible, but challenging.

3-dimensions: as opposed to the 2-dimensions needed to follow a road, where you can assume clearance above and to the sides, we have to consider heights. The Personal Transport Vehicle needs to decide how close to the table to get so my father can eat. Will the arms of the Personal Transport Vehicle fit under the table? Are my father’s hands in the way? We’re talking less than an inch, and in all 3-dimensions, not just a path on the floor.

Time, the 4^th-dimension: how fast does the situation change? Other Personal Transport Vehicles are moving at up to 10 mph (15 feet/second). People are moving half that fast. The path to my father’s table can change dramatically as other people jostle for position to get to their tables – have you ever seen the start of the dinner hour at a senior facility? J

Time is even more complex because we have other events to consider than just local motion: what time does dinner open and close? Does my father have a reservation for a specific time? Is he meeting people for dinner? Are they on time, or early or late? Based on past experience how long will it take to get to the dining room from his apartment? How many other people have reservations at the same time? Is there a party or other event going on in the dining room to make it more crowded, or to draw people to some other site? If he is late will they be out of his favorite dish?

As we expand this situation to include other vehicles and Convoys at much higher speeds, and other types of events and locations, you can see that this is a major challenge.

So what we need is a detailed 3-dimensional model of the world plus continuous updates to include moving and moveable objects. We also need to keep data on the past to predict things like traffic levels, on-time data for scheduled transport, and your favorite trips so you don’t have to keep entering them.

What about the future? We want to know about schedules and reservations and menus for restaurants; when businesses are having sales on particular items; and a myriad other things.

So you can see why I'm proposing a detailed 4-Dimensional map, as essential for helping my father, and all the rest of us too.

Let’s start with ideas for the location challenge, and later I’ll expand to the other challenges.

Existing Examples of Personal Transport Vehicles

So far I’ve talked about Personal Transport Vehicles based on chairs.

Our friends recommended a cute French movie Intouchables based on a true story of a quadriplegic and his caregiver. In search of his previous life of speed and daring, they soup up a wheelchair and speed past a Segway. 

But I had a revelation of the innovation in Personal Transport Vehicles on a trip to Portland Oregon. Browsing through the inflight catalog on the United flight, I saw a cool looking device called the Solowheel. But I’m always skeptical of things I see in those catalogs, in part because my daughter and I have a pet project of building a catalog of improbable things. 

While walking in the Portland Airport, I saw someone moving quite fast on the powered walkway – and his head wasn’t moving as it would be if he were walking rapidly. As he popped out at the end of the walkway, voila he was on a Solowheel! I watched him disappear down the hall. Later I saw him stop, pick up the Solowheel, fold up the steps, and board an airplane – I knew I had to blog about it. There are some videos on the Solowheel website which I recommend so you can see how easy this is to use – I wouldn’t believe it if I hadn’t seen it in person, so I hope you enjoy them. 

While browsing, I got drawn in by self-balancing unicycles. One that intrigued me is the Enicycle. This shows progress toward a portable Personal Transport Vehicle that doesn’t require the skills of a skateboarder to keep from falling over, and that allows you to sit down while traveling. The video shows how easy this is to use, and how it can be used in everyday life. He doesn’t ride it onto the train, but he does carry it aboard, showing at least a partial demonstration of Hierarchical Nesting.

As usual, YouTube will lead you to some other interesting vehicles, if you are so inclined.

One is a protoype Toyota Riding Machine, sort of a portable Segway, being tested by Toyota. The thing that intrigued me was a comment by the announcer that Toyota says in the future it can be automated to take you where you need to go – and you thought I was just dreaming!

I’m sure there are other innovative ideas to come, but hopefully this establishes that several of the building blocks of my proposed Transportation System are just around the corner. 

So let’s get on with other aspects of the Transportation System and the impacts on our everyday lives.